{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Source of the materials**: Biopython cookbook (adapted)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#Lets load notebook's Image\n",
    "from IPython.core.display import Image "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from reportlab.lib import colors\n",
    "from reportlab.lib.units import cm\n",
    "from Bio.Graphics import GenomeDiagram\n",
    "from Bio import SeqIO"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Graphics including GenomeDiagram"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Bio.Graphics module depends on the third party Python library ReportLab. Although focused on producing PDF files, ReportLab can also create encapsulated postscript (EPS) and (SVG) files. In addition to these vector based images, provided certain further dependencies such as the Python Imaging Library (PIL) are installed, ReportLab can also output bitmap images (including JPEG, PNG, GIF, BMP and PICT formats)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## GenomeDiagram"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Introduction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The **Bio.Graphics.GenomeDiagram** module was added to Biopython 1.50, having previously been available as a separate Python module dependent on Biopython.\n",
    "\n",
    "As the name might suggest, GenomeDiagram was designed for drawing whole genomes, in particular prokaryotic genomes, either as linear diagrams (optionally broken up into fragments to fit better) or as circular wheel diagrams. It proved also well suited to drawing quite detailed figures for smaller genomes such as phage, plasmids or mitochrondia.\n",
    "\n",
    "This module is easiest to use if you have your genome loaded as a SeqRecord object containing lots of SeqFeature objects - for example as loaded from a GenBank file."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Diagrams, tracks, feature-sets and features"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "GenomeDiagram uses a nested set of objects. At the top level, you have a diagram object representing a sequence (or sequence region) along the horizontal axis (or circle). A diagram can contain one or more tracks, shown stacked vertically (or radially on circular diagrams). These will typically all have the same length and represent the same sequence region. You might use one track to show the gene locations, another to show regulatory regions, and a third track to show the GC percentage.\n",
    "\n",
    "The most commonly used type of track will contain features, bundled together in feature-sets. You might choose to use one feature-set for all your CDS features, and another for tRNA features. This isn’t required - they can all go in the same feature-set, but it makes it easier to update the properties of just selected features (e.g. make all the tRNA features red).\n",
    "\n",
    "There are two main ways to build up a complete diagram. Firstly, the top down approach where you create a diagram object, and then using its methods add track(s), and use the track methods to add feature-set(s), and use their methods to add the features. Secondly, you can create the individual objects separately (in whatever order suits your code), and then combine them."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### A top down example"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We’re going to draw a whole genome from a SeqRecord object read in from a GenBank file. This example uses the pPCP1 plasmid from Yersinia pestis biovar Microtus (<a href=\"data/NC_005816.gb\">NC_005816.gb</a>)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "record = SeqIO.read(\"data/NC_005816.gb\", \"genbank\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We’re using a top down approach, so after loading in our sequence we next create an empty diagram, then add an (empty) track, and to that add an (empty) feature set:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "gd_diagram = GenomeDiagram.Diagram(\"Yersinia pestis biovar Microtus plasmid pPCP1\")\n",
    "gd_track_for_features = gd_diagram.new_track(1, name=\"Annotated Features\")\n",
    "gd_feature_set = gd_track_for_features.new_set()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now the fun part - we take each gene SeqFeature object in our SeqRecord, and use it to generate a feature on the diagram. We’re going to color them blue, alternating between a dark blue and a light blue."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for feature in record.features:\n",
    "    if feature.type != \"gene\":\n",
    "        #Exclude this feature\n",
    "        continue\n",
    "    if len(gd_feature_set) % 2 == 0:\n",
    "        color = colors.blue\n",
    "    else:\n",
    "        color = colors.lightblue\n",
    "    gd_feature_set.add_feature(feature, color=color, label=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we come to actually making the output file. This happens in two steps, first we call the draw method, which creates all the shapes using ReportLab objects. Then we call the write method which renders these to the requested file format. Note you can output in multiple file formats:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "gd_diagram.draw(format=\"linear\", orientation=\"landscape\", pagesize='A4',\n",
    "                fragments=4, start=0, end=len(record))\n",
    "gd_diagram.write(\"data/plasmid_linear.png\", \"png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lets have a look at the previous one:\n",
    "<img src=\"plasmid_linear.png\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice that the fragments argument which we set to four controls how many pieces the genome gets broken up into.\n",
    "\n",
    "If you want to do a circular figure, then try this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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MKVNas23nlfO/j13+vWmXpdIMez8l53W2xoRtIoRMSywWnzxyOPzgL/cvnzdD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\nSLgwpRBCCAkXphRCCCHhwpRCCCEkXP8HK836aZigbwsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gd_diagram.draw(format=\"circular\", circular=True, pagesize=(20*cm,20*cm),\n",
    "                start=0, end=len(record), circle_core=0.7)\n",
    "gd_diagram.write(\"data/plasmid_circular.png\", \"PNG\")\n",
    "Image(\"data/plasmid_circular.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These figures are not very exciting, but we’ve only just got started."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### A bottom up example"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let’s produce exactly the same figures, but using the bottom up approach. This means we create the different objects directly (and this can be done in almost any order) and then combine them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "record = SeqIO.read(\"data/NC_005816.gb\", \"genbank\")\n",
    "\n",
    "#Create the feature set and its feature objects,\n",
    "gd_feature_set = GenomeDiagram.FeatureSet()\n",
    "for feature in record.features:\n",
    "    if feature.type != \"gene\":\n",
    "        #Exclude this feature\n",
    "        continue\n",
    "    if len(gd_feature_set) % 2 == 0:\n",
    "        color = colors.blue\n",
    "    else:\n",
    "        color = colors.lightblue\n",
    "    gd_feature_set.add_feature(feature, color=color, label=True)\n",
    "#(this for loop is the same as in the previous example)\n",
    "\n",
    "#Create a track, and a diagram\n",
    "gd_track_for_features = GenomeDiagram.Track(name=\"Annotated Features\")\n",
    "gd_diagram = GenomeDiagram.Diagram(\"Yersinia pestis biovar Microtus plasmid pPCP1\")\n",
    "\n",
    "#Now have to glue the bits together...\n",
    "gd_track_for_features.add_set(gd_feature_set)\n",
    "gd_diagram.add_track(gd_track_for_features, 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can now call the draw and write methods as before to produce a linear or circular diagram, using the code at the end of the top-down example above. The figures should be identical."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Features without a SeqFeature"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the above example we used a SeqRecord’s SeqFeature objects to build our diagram. Sometimes you won’t have SeqFeature objects, but just the coordinates for a feature you want to draw. You have to create minimal SeqFeature object, but this is easy:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from Bio.SeqFeature import SeqFeature, FeatureLocation\n",
    "my_seq_feature = SeqFeature(FeatureLocation(50,100),strand=+1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For strand, use +1 for the forward strand, -1 for the reverse strand, and None for both. Here is a short self contained example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAakAAABxCAIAAADgVMv6AAAJBklEQVR4nO3cbWxM+QLH8XNmOp12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\n+wDIiPYBkNG/Afzo+VludggPAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gdd = GenomeDiagram.Diagram('Test Diagram')\n",
    "gdt_features = gdd.new_track(1, greytrack=False)\n",
    "gds_features = gdt_features.new_set()\n",
    "\n",
    "#Add three features to show the strand options,\n",
    "feature = SeqFeature(FeatureLocation(25, 125), strand=+1)\n",
    "gds_features.add_feature(feature, name=\"Forward\", label=True)\n",
    "feature = SeqFeature(FeatureLocation(150, 250), strand=None)\n",
    "gds_features.add_feature(feature, name=\"Strandless\", label=True)\n",
    "feature = SeqFeature(FeatureLocation(275, 375), strand=-1)\n",
    "gds_features.add_feature(feature, name=\"Reverse\", label=True)\n",
    "\n",
    "gdd.draw(format='linear', pagesize=(15*cm,4*cm), fragments=1,\n",
    "         start=0, end=400)\n",
    "gdd.write(\"data/GD_labels_default.png\", \"png\")\n",
    "Image(\"data/GD_labels_default.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The top part of the image in the next subsection shows the output (in the default feature color, pale green).\n",
    "\n",
    "Notice that we have used the name argument here to specify the caption text for these features. This is discussed in more detail next."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feature captions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Recall we used the following (where feature was a SeqFeature object) to add a feature to the diagram:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Bio.Graphics.GenomeDiagram._Feature.Feature at 0x7f27bfa2bfd0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gd_feature_set.add_feature(feature, color=color, label=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the example above the SeqFeature annotation was used to pick a sensible caption for the features. By default the following possible entries under the SeqFeature object’s qualifiers dictionary are used: gene, label, name, locus_tag, and product. More simply, you can specify a name directly:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Bio.Graphics.GenomeDiagram._Feature.Feature at 0x7f27bfa3b048>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gd_feature_set.add_feature(feature, color=color, label=True, name=\"My Gene\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In addition to the caption text for each feature’s label, you can also choose the font, position (this defaults to the start of the sigil, you can also choose the middle or at the end) and orientation (for linear diagrams only, where this defaults to rotated by 45 degrees):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Bio.Graphics.GenomeDiagram._Feature.Feature at 0x7f27cc0b2d30>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Large font, parallel with the track\n",
    "gd_feature_set.add_feature(feature, label=True, color=\"green\",\n",
    "                           label_size=25, label_angle=0)\n",
    "\n",
    "#Very small font, perpendicular to the track (towards it)\n",
    "gd_feature_set.add_feature(feature, label=True, color=\"purple\",\n",
    "                           label_position=\"end\",\n",
    "                           label_size=4, label_angle=90)\n",
    "\n",
    "#Small font, perpendicular to the track (away from it)\n",
    "gd_feature_set.add_feature(feature, label=True, color=\"blue\",\n",
    "                           label_position=\"middle\",\n",
    "                           label_size=6, label_angle=-90)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Combining each of these three fragments with the complete example in the previous section should give something like this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAakAAABxCAIAAADgVMv6AAAJBklEQVR4nO3cbWxM+QLH8XNmOp12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\n+wDIiPYBkNG/Afzo+VludggPAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gdd.draw(format='linear', pagesize=(15*cm,4*cm), fragments=1,\n",
    "         start=0, end=400)\n",
    "gdd.write(\"data/GD_labels.png\", \"png\")\n",
    "Image(\"data/GD_labels.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We’ve not shown it here, but you can also set label_color to control the label’s color.\n",
    "\n",
    "You’ll notice the default font is quite small - this makes sense because you will usually be drawing many (small) features on a page, not just a few large ones as shown here."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feature sigils"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The examples above have all just used the default sigil for the feature, a plain box, which was all that was available in the last publicly released standalone version of GenomeDiagram. Arrow sigils were included when GenomeDiagram was added to Biopython 1.50:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Bio.Graphics.GenomeDiagram._Feature.Feature at 0x7f27bfa3a7f0>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Default uses a BOX sigil\n",
    "gd_feature_set.add_feature(feature)\n",
    "\n",
    "#You can make this explicit:\n",
    "gd_feature_set.add_feature(feature, sigil=\"BOX\")\n",
    "\n",
    "#Or opt for an arrow:\n",
    "gd_feature_set.add_feature(feature, sigil=\"ARROW\")\n",
    "\n",
    "#Box with corners cut off (making it an octagon)\n",
    "gd_feature_set.add_feature(feature, sigil=\"OCTO\")\n",
    "\n",
    "#Box with jagged edges (useful for showing breaks in contains)\n",
    "gd_feature_set.add_feature(feature, sigil=\"JAGGY\")\n",
    "\n",
    "#Arrow which spans the axis with strand used only for direction\n",
    "gd_feature_set.add_feature(feature, sigil=\"BIGARROW\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These are shown below. Most sigils fit into a bounding box (as given by the default BOX sigil), either above or below the axis for the forward or reverse strand, or straddling it (double the height) for strand-less features. The BIGARROW sigil is different, always straddling the axis with the direction taken from the feature’s stand."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Arrow sigils"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We introduced the arrow sigils in the previous section. There are two additional options to adjust the shapes of the arrows, firstly the thickness of the arrow shaft, given as a proportion of the height of the bounding box:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Bio.Graphics.GenomeDiagram._Feature.Feature at 0x7f27cc0c0400>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Full height shafts, giving pointed boxes:\n",
    "gd_feature_set.add_feature(feature, sigil=\"ARROW\", color=\"brown\",\n",
    "                           arrowshaft_height=1.0)\n",
    "#Or, thin shafts:                      \n",
    "gd_feature_set.add_feature(feature, sigil=\"ARROW\", color=\"teal\",\n",
    "                           arrowshaft_height=0.2)\n",
    "#Or, very thin shafts:\n",
    "gd_feature_set.add_feature(feature, sigil=\"ARROW\", color=\"darkgreen\",\n",
    "                           arrowshaft_height=0.1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The results are shown below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Secondly, the length of the arrow head - given as a proportion of the height of the bounding box (defaulting to 0.5, or 50%):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Bio.Graphics.GenomeDiagram._Feature.Feature at 0x7f27cc0bc208>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Short arrow heads:\n",
    "gd_feature_set.add_feature(feature, sigil=\"ARROW\", color=\"blue\",\n",
    "                           arrowhead_length=0.25)\n",
    "#Or, longer arrow heads:\n",
    "gd_feature_set.add_feature(feature, sigil=\"ARROW\", color=\"orange\",\n",
    "                           arrowhead_length=1)\n",
    "#Or, very very long arrow heads (i.e. all head, no shaft, so triangles):\n",
    "gd_feature_set.add_feature(feature, sigil=\"ARROW\", color=\"red\",\n",
    "                           arrowhead_length=10000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The results are shown below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Biopython 1.61 adds a new BIGARROW sigil which always stradles the axis, pointing left for the reverse strand or right otherwise:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Bio.Graphics.GenomeDiagram._Feature.Feature at 0x7f27bfa2be80>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#A large arrow straddling the axis:\n",
    "gd_feature_set.add_feature(feature, sigil=\"BIGARROW\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "All the shaft and arrow head options shown above for the ARROW sigil can be used for the BIGARROW sigil too."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### A nice example"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let’s return to the pPCP1 plasmid from Yersinia pestis biovar Microtus, and the top down approach used above, but take advantage of the sigil options we’ve now discussed. This time we’ll use arrows for the genes, and overlay them with strand-less features (as plain boxes) showing the position of some restriction digest sites."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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dy8vL3g/OZpgznl/6/EsrX9p7dW/g94GRtyLV5R9t/SgpPUnb2WA7UlJSqlSp4u7ufuLE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\ns7gAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "record = SeqIO.read(\"data/NC_005816.gb\", \"genbank\")\n",
    "\n",
    "gd_diagram = GenomeDiagram.Diagram(record.id)\n",
    "gd_track_for_features = gd_diagram.new_track(1, name=\"Annotated Features\")\n",
    "gd_feature_set = gd_track_for_features.new_set()\n",
    "\n",
    "for feature in record.features:\n",
    "    if feature.type != \"gene\":\n",
    "        #Exclude this feature\n",
    "        continue\n",
    "    if len(gd_feature_set) % 2 == 0:\n",
    "        color = colors.blue\n",
    "    else:\n",
    "        color = colors.lightblue\n",
    "    gd_feature_set.add_feature(feature, sigil=\"ARROW\",\n",
    "                               color=color, label=True,\n",
    "                               label_size = 14, label_angle=0)\n",
    "\n",
    "#I want to include some strandless features, so for an example\n",
    "#will use EcoRI recognition sites etc.\n",
    "for site, name, color in [(\"GAATTC\",\"EcoRI\",colors.green),\n",
    "                          (\"CCCGGG\",\"SmaI\",colors.orange),\n",
    "                          (\"AAGCTT\",\"HindIII\",colors.red),\n",
    "                          (\"GGATCC\",\"BamHI\",colors.purple)]:\n",
    "    index = 0\n",
    "    while True:\n",
    "        index  = record.seq.find(site, start=index)\n",
    "        if index == -1 : break\n",
    "        feature = SeqFeature(FeatureLocation(index, index+len(site)))\n",
    "        gd_feature_set.add_feature(feature, color=color, name=name,\n",
    "                                   label=True, label_size = 10,\n",
    "                                   label_color=color)\n",
    "        index += len(site)\n",
    "\n",
    "gd_diagram.draw(format=\"linear\", pagesize='A4', fragments=4,\n",
    "                start=0, end=len(record))\n",
    "gd_diagram.write(\"data/plasmid_linear_nice.png\", \"png\")\n",
    "\n",
    "Image(\"data/plasmid_linear_nice.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ffC3QYFa1U1EBVKqGpZR0gtepU3DtGuA4jB8PEyaArsO7hMIEU5ZpJ7tOqi5QA3Tp0uXx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8Og61b95ujRo62srP78808VFoggiFJMmTJFS0tr586dqi6kSUAppRQEfPwHXs4BUQXQjcB/D9h+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\nBEGUF8pSCIIgiPL6f0EFqri5zjcdAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gd_diagram.draw(format=\"circular\", circular=True, pagesize=(20*cm,20*cm),\n",
    "                start=0, end=len(record), circle_core = 0.5)\n",
    "gd_diagram.write(\"data/plasmid_circular_nice.png\", \"png\")\n",
    "\n",
    "Image(\"data/plasmid_circular_nice.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Multiple tracks"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "All the examples so far have used a single track, but you can have more than one track – for example show the genes on one, and repeat regions on another. In this example we’re going to show three phage genomes side by side to scale, inspired by Figure 6 in Proux et al. (2002). We’ll need the GenBank files for the following three phage:\n",
    "\n",
    "- NC_002703 – Lactococcus phage Tuc2009, complete genome (38347 bp)\n",
    "- AF323668 – Bacteriophage bIL285, complete genome (35538 bp)\n",
    "- NC_003212 – Listeria innocua Clip11262, complete genome, of which we are focussing only on integrated prophage 5 (similar length).\n",
    "\n",
    "You can download these using Entrez if you like. For the third record we’ve worked out where the phage is integrated into the genome, and slice the record to extract it, and must also reverse complement to match the orientation of the first two phage:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "A_rec = SeqIO.read(\"data/NC_002703.gbk\", \"gb\")\n",
    "B_rec = SeqIO.read(\"data/AF323668.gbk\", \"gb\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The figure we are imitating used different colors for different gene functions. One way to do this is to edit the GenBank file to record color preferences for each feature - something Sanger’s Artemis editor does, and which GenomeDiagram should understand. Here however, we’ll just hard code three lists of colors.\n",
    "\n",
    "Note that the annotation in the GenBank files doesn’t exactly match that shown in Proux et al., they have drawn some unannotated genes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from reportlab.lib.colors import red, grey, orange, green, brown, blue, lightblue, purple\n",
    "\n",
    "A_colors = [red]*5 + [grey]*7 + [orange]*2 + [grey]*2 + [orange] + [grey]*11 + [green]*4 \\\n",
    "         + [grey] + [green]*2 + [grey, green] + [brown]*5 + [blue]*4 + [lightblue]*5 \\\n",
    "         + [grey, lightblue] + [purple]*2 + [grey]\n",
    "B_colors = [red]*6 + [grey]*8 + [orange]*2 + [grey] + [orange] + [grey]*21 + [green]*5 \\\n",
    "         + [grey] + [brown]*4 + [blue]*3 + [lightblue]*3 + [grey]*5 + [purple]*2\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now to draw them – this time we add three tracks to the diagram, and also notice they are given different start/end values to reflect their different lengths."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Se6vi2b59u82RfOVW/YeUUs0dRCV2mQUCAcsUATUpWIMsy2YZISpm+il+dZRS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D7//PMDBgxQT36zwdnZ2WeeeeaCBQsWLVq0d+/eAQMGNCp5FwwGx4wZk56e/vTTT8f2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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name = \"data/Proux Fig 6\"\n",
    "gd_diagram = GenomeDiagram.Diagram(name)\n",
    "max_len = 0\n",
    "for record, gene_colors in zip([A_rec, B_rec], [A_colors, B_colors]):\n",
    "    max_len = max(max_len, len(record))\n",
    "    gd_track_for_features = gd_diagram.new_track(1,\n",
    "                            name=record.name,\n",
    "                            greytrack=True,\n",
    "                            start=0, end=len(record))\n",
    "    gd_feature_set = gd_track_for_features.new_set()\n",
    "\n",
    "    i = 0\n",
    "    for feature in record.features:\n",
    "        if feature.type != \"gene\":\n",
    "            #Exclude this feature                                                                                                   \n",
    "            continue\n",
    "        gd_feature_set.add_feature(feature, sigil=\"ARROW\",\n",
    "                                   color=gene_colors[i], label=True,\n",
    "                                   name = str(i+1),\n",
    "                                   label_position=\"start\",\n",
    "                                   label_size = 6, label_angle=0)\n",
    "        i+=1\n",
    "\n",
    "gd_diagram.draw(format=\"linear\", pagesize='A4', fragments=1,\n",
    "                start=0, end=max_len)\n",
    "gd_diagram.write(name + \".png\", \"png\")\n",
    "Image(name + \".png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I did wonder why in the original manuscript there were no red or orange genes marked in the bottom phage. Another important point is here the phage are shown with different lengths - this is because they are all drawn to the same scale (they are different lengths).\n",
    "\n",
    "The key difference from the published figure is they have color-coded links between similar proteins – which is what we will do in the next section."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cross-Links between tracks"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Biopython 1.59 added the ability to draw cross links between tracks - both simple linear diagrams as we will show here, but also linear diagrams split into fragments and circular diagrams.\n",
    "\n",
    "Continuing the example from the previous section inspired by Figure 6 from Proux et al. 2002, we would need a list of cross links between pairs of genes, along with a score or color to use. Realistically you might extract this from a BLAST file computationally, but here I have manually typed them in.\n",
    "\n",
    "My naming convention continues to refer to the three phage as A, B and C. Here are the links we want to show between A and B, given as a list of tuples (percentage similarity score, gene in A, gene in B)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#Tuc2009 (NC_002703) vs bIL285 (AF323668)\n",
    "A_vs_B = [\n",
    "    (99, \"Tuc2009_01\", \"int\"),\n",
    "    (33, \"Tuc2009_03\", \"orf4\"),\n",
    "    (94, \"Tuc2009_05\", \"orf6\"),\n",
    "    (100,\"Tuc2009_06\", \"orf7\"),\n",
    "    (97, \"Tuc2009_07\", \"orf8\"),\n",
    "    (98, \"Tuc2009_08\", \"orf9\"),\n",
    "    (98, \"Tuc2009_09\", \"orf10\"),\n",
    "    (100,\"Tuc2009_10\", \"orf12\"),\n",
    "    (100,\"Tuc2009_11\", \"orf13\"),\n",
    "    (94, \"Tuc2009_12\", \"orf14\"),\n",
    "    (87, \"Tuc2009_13\", \"orf15\"),\n",
    "    (94, \"Tuc2009_14\", \"orf16\"),\n",
    "    (94, \"Tuc2009_15\", \"orf17\"),\n",
    "    (88, \"Tuc2009_17\", \"rusA\"),\n",
    "    (91, \"Tuc2009_18\", \"orf20\"),\n",
    "    (93, \"Tuc2009_19\", \"orf22\"),\n",
    "    (71, \"Tuc2009_20\", \"orf23\"),\n",
    "    (51, \"Tuc2009_22\", \"orf27\"),\n",
    "    (97, \"Tuc2009_23\", \"orf28\"),\n",
    "    (88, \"Tuc2009_24\", \"orf29\"),\n",
    "    (26, \"Tuc2009_26\", \"orf38\"),\n",
    "    (19, \"Tuc2009_46\", \"orf52\"),\n",
    "    (77, \"Tuc2009_48\", \"orf54\"),\n",
    "    (91, \"Tuc2009_49\", \"orf55\"),\n",
    "    (95, \"Tuc2009_52\", \"orf60\"), \n",
    "]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For the first and last phage these identifiers are locus tags, for the middle phage there are no locus tags so I’ve used gene names instead. The following little helper function lets us lookup a feature using either a locus tag or gene name:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def get_feature(features, id, tags=[\"locus_tag\", \"gene\"]):\n",
    "    \"\"\"Search list of SeqFeature objects for an identifier under the given tags.\"\"\"\n",
    "    for f in features:\n",
    "        for key in tags:\n",
    "            #tag may not be present in this feature \n",
    "            for x in f.qualifiers.get(key, []):\n",
    "                if x == id:\n",
    "                     return f\n",
    "    raise KeyError(id)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can now turn those list of identifier pairs into SeqFeature pairs, and thus find their location co-ordinates. We can now add all that code and the following snippet to the previous example (just before the gd_diagram.draw(...) line – see the finished example script <a href=\"data/Proux_et_al_2002_Figure_6.py\">Proux_et_al_2002_Figure_6.py</a> included in the Doc/examples folder of the Biopython source code) to add cross links to the figure:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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81z20n9t2zhfs37V5c+Dky5dHy9MNGwKeEZzD5s3VPhsNA775Tf2nP+1ni5fJ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\nc89lhQITYmoqtS6bnTp9ekNDQ1dX16RJk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xavmSbZjs1DDz00ePDgKFkzbeO9ysEl+TOe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\nFP8fjiwdO67EkoMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from Bio.Graphics.GenomeDiagram import CrossLink\n",
    "from reportlab.lib import colors\n",
    "#Note it might have been clearer to assign the track numbers explicitly...                                                          \n",
    "for rec_X, tn_X, rec_Y, tn_Y, X_vs_Y in [(A_rec, 2, B_rec, 1, A_vs_B)]:\n",
    "    track_X = gd_diagram.tracks[tn_X]\n",
    "    track_Y = gd_diagram.tracks[tn_Y]\n",
    "    for score, id_X, id_Y in X_vs_Y:\n",
    "        feature_X = get_feature(rec_X.features, id_X)\n",
    "        feature_Y = get_feature(rec_Y.features, id_Y)\n",
    "        color = colors.linearlyInterpolatedColor(colors.white, colors.firebrick, 0, 100, score)\n",
    "        link_xy = CrossLink((track_X, feature_X.location.start, feature_X.location.end),\n",
    "                            (track_Y, feature_Y.location.start, feature_Y.location.end),\n",
    "                            color, colors.lightgrey)\n",
    "        gd_diagram.cross_track_links.append(link_xy)\n",
    "gd_diagram.draw(format=\"linear\", pagesize='A4', fragments=1,\n",
    "                start=0, end=max_len)\n",
    "gd_diagram.write(\"data/cross.png\", \"png\")\n",
    "Image(\"data/cross.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are several important pieces to this code. First the GenomeDiagram object has a cross_track_links attribute which is just a list of CrossLink objects. Each CrossLink object takes two sets of track-specific co-ordinates (here given as tuples, you can alternatively use a GenomeDiagram.Feature object instead). You can optionally supply a colour, border color, and say if this link should be drawn flipped (useful for showing inversions).\n",
    "\n",
    "You can also see how we turn the BLAST percentage identity score into a colour, interpolating between white (0%) and a dark red (100%). In this example we don’t have any problems with overlapping cross-links. One way to tackle that is to use transparency in ReportLab, by using colors with their alpha channel set. However, this kind of shaded color scheme combined with overlap transparency would be difficult to interpret. The result:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There is still a lot more that can be done within Biopython to help improve this figure. First of all, the cross links in this case are between proteins which are drawn in a strand specific manor. It can help to add a background region (a feature using the ‘BOX’ sigil) on the feature track to extend the cross link. Also, we could reduce the vertical height of the feature tracks to allocate more to the links instead – one way to do that is to allocate space for empty tracks. Furthermore, in cases like this where there are no large gene overlaps, we can use the axis-straddling BIGARROW sigil, which allows us to further reduce the vertical space needed for the track. These improvements are demonstrated in the example script <a href=\"data/Proux_et_al_2002_Figure_6.py\">Proux_et_al_2002_Figure_6.py</a>."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Beyond that, finishing touches you might want to do manually in a vector image editor include fine tuning the placement of gene labels, and adding other custom annotation such as highlighting particular regions.\n",
    "\n",
    "Although not really necessary in this example since none of the cross-links overlap, using a transparent color in ReportLab is a very useful technique for superimposing multiple links. However, in this case a shaded color scheme should be avoided."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Chromosomes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Bio.Graphics.BasicChromosome module allows drawing of chromosomes. There is an example in Jupe et al. (2012) (open access) using colors to highlight different gene families."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Simple Chromosomes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Important**: To continue this example you have first to download a few chromosomes from Arabidopsis thaliana, the code to help you is here:\n",
    "\n",
    "**Very important**: This is slow and clogs the network, you only need to do this once (even if you close the notebook as the download will be persistent)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from ftplib import FTP\n",
    "ftp = FTP('ftp.ncbi.nlm.nih.gov')\n",
    "print(\"Logging in\")\n",
    "ftp.login()\n",
    "ftp.cwd('genomes/archive/old_genbank/A_thaliana/OLD/')\n",
    "print(\"Starting download - This can be slow!\")\n",
    "for chro, name in [\n",
    "        (\"CHR_I\", \"NC_003070.fna\"), (\"CHR_I\", \"NC_003070.gbk\"),\n",
    "        (\"CHR_II\", \"NC_003071.fna\"), (\"CHR_II\", \"NC_003071.gbk\"),\n",
    "        (\"CHR_III\", \"NC_003072.fna\"), (\"CHR_III\", \"NC_003072.gbk\"),\n",
    "        (\"CHR_IV\", \"NC_003073.fna\"), (\"CHR_IV\", \"NC_003073.gbk\"),\n",
    "        (\"CHR_V\", \"NC_003074.fna\"), (\"CHR_V\", \"NC_003074.gbk\")]:\n",
    "    print(\"Downloading\", chro, name)\n",
    "    ftp.retrbinary('RETR %s/%s' % (chro, name), open('data/%s' % name, 'wb').write)\n",
    "ftp.quit()\n",
    "print('Done')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here is a very simple example - for which we’ll use Arabidopsis thaliana.\n",
    "\n",
    "You can skip this bit, but first I downloaded the five sequenced chromosomes from the NCBI’s FTP site (per the code above) and then parsed them with Bio.SeqIO to find out their lengths. You could use the GenBank files for this, but it is faster to use the FASTA files for the whole chromosomes:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from Bio import SeqIO\n",
    "entries = [(\"Chr I\", \"NC_003070.fna\"),\n",
    "           (\"Chr II\", \"NC_003071.fna\"),\n",
    "           (\"Chr III\", \"NC_003072.fna\"),\n",
    "           (\"Chr IV\", \"NC_003073.fna\"),\n",
    "           (\"Chr V\", \"NC_003074.fna\")]\n",
    "for (name, filename) in entries:\n",
    "   record = SeqIO.read(\"data/\" + filename, \"fasta\")\n",
    "   print(name, len(record))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This gave the lengths of the five chromosomes, which we’ll now use in the following short demonstration of the BasicChromosome module:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from reportlab.lib.units import cm\n",
    "from Bio.Graphics import BasicChromosome\n",
    "\n",
    "entries = [(\"Chr I\", 30432563),\n",
    "           (\"Chr II\", 19705359),\n",
    "           (\"Chr III\", 23470805),\n",
    "           (\"Chr IV\", 18585042),\n",
    "           (\"Chr V\", 26992728)]\n",
    "\n",
    "max_len = 30432563 #Could compute this\n",
    "telomere_length = 1000000 #For illustration\n",
    "         \n",
    "chr_diagram = BasicChromosome.Organism(output_format=\"png\")\n",
    "chr_diagram.page_size = (29.7*cm, 21*cm) #A4 landscape\n",
    "\n",
    "for name, length in entries:\n",
    "    cur_chromosome = BasicChromosome.Chromosome(name)\n",
    "    #Set the scale to the MAXIMUM length plus the two telomeres in bp,\n",
    "    #want the same scale used on all five chromosomes so they can be\n",
    "    #compared to each other\n",
    "    cur_chromosome.scale_num = max_len + 2 * telomere_length\n",
    "\n",
    "    #Add an opening telomere\n",
    "    start = BasicChromosome.TelomereSegment()\n",
    "    start.scale = telomere_length\n",
    "    cur_chromosome.add(start)\n",
    "\n",
    "    #Add a body - using bp as the scale length here.\n",
    "    body = BasicChromosome.ChromosomeSegment()\n",
    "    body.scale = length\n",
    "    cur_chromosome.add(body)\n",
    "\n",
    "    #Add a closing telomere\n",
    "    end = BasicChromosome.TelomereSegment(inverted=True)\n",
    "    end.scale = telomere_length\n",
    "    cur_chromosome.add(end)\n",
    "\n",
    "    #This chromosome is done\n",
    "    chr_diagram.add(cur_chromosome)\n",
    "\n",
    "chr_diagram.draw(\"data/simple_chrom.png\", \"Arabidopsis thaliana\")\n",
    "Image(\"data/simple_chrom.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This example is deliberately short and sweet. The next example shows the location of features of interest."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Continuing from the previous example, let’s also show the tRNA genes. We’ll get their locations by parsing the GenBank files for the five Arabidopsis thaliana chromosomes. You’ll need to download these files from the NCBI FTP site."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "entries = [(\"Chr I\", \"NC_003070.gbk\"),\n",
    "           (\"Chr II\", \"NC_003071.gbk\"),\n",
    "           (\"Chr III\", \"NC_003072.gbk\"),\n",
    "           (\"Chr IV\", \"NC_003073.gbk\"),\n",
    "           (\"Chr V\", \"NC_003074.gbk\")]\n",
    "\n",
    "max_len = 30432563 #Could compute this\n",
    "telomere_length = 1000000 #For illustration\n",
    "\n",
    "chr_diagram = BasicChromosome.Organism(output_format=\"png\")\n",
    "chr_diagram.page_size = (29.7*cm, 21*cm) #A4 landscape\n",
    "\n",
    "for index, (name, filename) in enumerate(entries):\n",
    "    record = SeqIO.read(\"data/\" + filename,\"genbank\")\n",
    "    length = len(record)\n",
    "    features = [f for f in record.features if f.type==\"tRNA\"]\n",
    "    #Record an Artemis style integer color in the feature's qualifiers,\n",
    "    #1 = Black, 2 = Red, 3 = Green, 4 = blue, 5 =cyan, 6 = purple \n",
    "    for f in features: f.qualifiers[\"color\"] = [index+2]\n",
    "\n",
    "    cur_chromosome = BasicChromosome.Chromosome(name)\n",
    "    #Set the scale to the MAXIMUM length plus the two telomeres in bp,\n",
    "    #want the same scale used on all five chromosomes so they can be\n",
    "    #compared to each other\n",
    "    cur_chromosome.scale_num = max_len + 2 * telomere_length\n",
    "\n",
    "    #Add an opening telomere\n",
    "    start = BasicChromosome.TelomereSegment()\n",
    "    start.scale = telomere_length\n",
    "    cur_chromosome.add(start)\n",
    "\n",
    "    #Add a body - again using bp as the scale length here.\n",
    "    body = BasicChromosome.AnnotatedChromosomeSegment(length, features)\n",
    "    body.scale = length\n",
    "    cur_chromosome.add(body)\n",
    "\n",
    "    #Add a closing telomere\n",
    "    end = BasicChromosome.TelomereSegment(inverted=True)\n",
    "    end.scale = telomere_length\n",
    "    cur_chromosome.add(end)\n",
    "\n",
    "    #This chromosome is done\n",
    "    chr_diagram.add(cur_chromosome)\n",
    "\n",
    "chr_diagram.draw(\"data/tRNA_chrom.png\", \"Arabidopsis thaliana\")\n",
    "Image(\"data/tRNA_chrom.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  }
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